Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation

Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation

This paper is concerned with the robust distributed H∞ filtering problem for nonlinear systems subject to sensor saturations and fractional parameter uncertainties. A sufficient condition is derived for the filtering error system to reach the required H∞ performance in terms of recursive linear matr...

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Main Authors: Dong Liu, Guangfu Tang, Zhiyuan He, Yan Zhao, Hui Pang
Format: Article
Language:English
Published: Hindawi Limited 2015-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2015/160683
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spelling doaj-5f06ad3e2df44793bdf90405ece426b32020-11-24T23:15:28ZengHindawi LimitedDiscrete Dynamics in Nature and Society1026-02261607-887X2015-01-01201510.1155/2015/160683160683Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital SimulationDong Liu0Guangfu Tang1Zhiyuan He2Yan Zhao3Hui Pang4State Grid Smart Grid Research Institute, North Zone of Future Sci-Tech City, Beiqijia, Changping District, Beijing 102211, ChinaState Grid Smart Grid Research Institute, North Zone of Future Sci-Tech City, Beiqijia, Changping District, Beijing 102211, ChinaState Grid Smart Grid Research Institute, North Zone of Future Sci-Tech City, Beiqijia, Changping District, Beijing 102211, ChinaState Grid Smart Grid Research Institute, North Zone of Future Sci-Tech City, Beiqijia, Changping District, Beijing 102211, ChinaState Grid Smart Grid Research Institute, North Zone of Future Sci-Tech City, Beiqijia, Changping District, Beijing 102211, ChinaThis paper is concerned with the robust distributed H∞ filtering problem for nonlinear systems subject to sensor saturations and fractional parameter uncertainties. A sufficient condition is derived for the filtering error system to reach the required H∞ performance in terms of recursive linear matrix inequality method. An iterative algorithm is then proposed to obtain the filter parameters recursively by solving the corresponding linear matrix inequality. A numerical example is presented to show the effectiveness of the proposed method.http://dx.doi.org/10.1155/2015/160683
collection DOAJ
language English
format Article
sources DOAJ
author Dong Liu
Guangfu Tang
Zhiyuan He
Yan Zhao
Hui Pang
spellingShingle Dong Liu
Guangfu Tang
Zhiyuan He
Yan Zhao
Hui Pang
Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation
Discrete Dynamics in Nature and Society
author_facet Dong Liu
Guangfu Tang
Zhiyuan He
Yan Zhao
Hui Pang
author_sort Dong Liu
title Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation
title_short Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation
title_full Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation
title_fullStr Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation
title_full_unstemmed Robust Distributed H∞ Filtering for Nonlinear Systems with Sensor Saturations and Fractional Uncertainties with Digital Simulation
title_sort robust distributed h∞ filtering for nonlinear systems with sensor saturations and fractional uncertainties with digital simulation
publisher Hindawi Limited
series Discrete Dynamics in Nature and Society
issn 1026-0226
1607-887X
publishDate 2015-01-01
description This paper is concerned with the robust distributed H∞ filtering problem for nonlinear systems subject to sensor saturations and fractional parameter uncertainties. A sufficient condition is derived for the filtering error system to reach the required H∞ performance in terms of recursive linear matrix inequality method. An iterative algorithm is then proposed to obtain the filter parameters recursively by solving the corresponding linear matrix inequality. A numerical example is presented to show the effectiveness of the proposed method.
url http://dx.doi.org/10.1155/2015/160683
work_keys_str_mv AT dongliu robustdistributedhfilteringfornonlinearsystemswithsensorsaturationsandfractionaluncertaintieswithdigitalsimulation
AT guangfutang robustdistributedhfilteringfornonlinearsystemswithsensorsaturationsandfractionaluncertaintieswithdigitalsimulation
AT zhiyuanhe robustdistributedhfilteringfornonlinearsystemswithsensorsaturationsandfractionaluncertaintieswithdigitalsimulation
AT yanzhao robustdistributedhfilteringfornonlinearsystemswithsensorsaturationsandfractionaluncertaintieswithdigitalsimulation
AT huipang robustdistributedhfilteringfornonlinearsystemswithsensorsaturationsandfractionaluncertaintieswithdigitalsimulation
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